Identification of Woodchuck Toll-like Receptors and Their Expression During the Course of Hepadnaviral Infection in the Woodchuck Model of Hepatitis B

Identification of Woodchuck Toll-like Receptors and Their Expression During the Course of Hepadnaviral Infection in the Woodchuck Model of

Hepatitis B

by

© John Bradley Williams

A thesis submitted to the School of Graduate Studies in partial fulfillment of the requirements for the

degree of Master of Science in Medicine

Faculty of Medicine

Memorial University of Newfoundland

May 2017

St. Johns Newfoundland

i Abstract

The woodchuck hepatitis virus (WHV) is closely related to human hepatitis B virus (HBV), the prototypic member of the Hepanaviridae family. Toll-like receptors (TLRs) may play an important role in the pathogenesis of hepadnaviral hepatitis, however, little is known about their expression during the course of hepadnaviral infection. In this study, woodchuck TLRs1-10 gene exon fragments were identified and their transcriptional profiles investigated in livers, hepatocytes isolated from these livers, and peripheral blood mononuclear cells (PBMCs) from healthy woodchucks and animals with different stages of experimental WHV infection. Overall expression analysis revealed that livers from woodchucks with acute hepatitis (AH) and chronic hepatitis (CH) had significantly upregulated expression of TLRs2-10 when compared to the livers of healthy animals and those with self-limited acute hepatitis (SLAH) and primary occult infection (POI). This was likely due to intrahepatic immune cell infiltration. In contrast, a significant downregulation of TLR3, TLR5, TLR7, TLR8, and TLR10 expression was identified in hepatocytes of woodchucks with CH when compared to hepatocytes from healthy animals and those with pre-acute hepatitis (PreAH), SLAH and POI. This may suggest WHV active suppression of the innate immune response in these cells. Upregulated transcription of the majority of TLRs was found in PBMCs during CH but not in other stages of infection. In summary, this study uncovered that TLR expression is significantly modulated depending on the stage of WHV infection and form of hepatitis. Treatments designed to restore hepatocyte TLR expression may allow for better control of the virus through activation of a stronger intrahepatocyte immune response during CH.

ii

Acknowledgements

During my Master’s degree I have had the opportunity to work with many knowledgeable and supporting individuals. First and foremost, I would like to thank Dr.

Thomas Michalak for providing me with the opportunity to pursue my graduate studies in his laboratory. His patience and guidance throughout my graduate degree has been nothing less than exceptional. I can honestly say that I am privileged to have had the opportunity to work under such a great scientific mentor.

I would also like to thank Dr. Patricia Mulrooney-Cousins for always being there.

She has provided me with a support system that hasn’t gone unnoticed. Whenever I have had a question about research, or life in general, she has always answered with honesty and positivity. I truly thank her for her friendship and mentorship during my time in the Michalak lab.

I would also like to thank my supervisory committee members Dr. Rodney Russell, Dr. Vernon Richardson, and Dr. Kensuke Hirasawa. They have provided me with guidance and encouragement during my Master’s degree, and for that, I thank them.

Additionally, I would like to thank all the people who worked in the Michalak lab during my time there. Whenever I needed assistance they were there to lend a helping hand. My experiences in this laboratory have provided me with crucial knowledge that will assist me in my future endeavors.

iii

I would also like to extend a big thank you to my family for their support throughout this program. Their encouragement and guidance was an important part of my success.

In closing, I would like to thank the Canadian Institute of Health Research for their generous support during this project. I would also like to thank the School of Graduate Studies at Memorial University for a student fellowship received.

iv

Table of Contents

Abstract ... i

Acknowledgements ... ii

List of Tables ... viii

List of Figures ... ix

List of Abbreviations ... xi

List of Appendices ... xiv

Chapter 1 – Introduction ... 15

1.1. Brief History of Studies on Hepatitis B Virus Identification ... 15

1.2. Epidemiology of HBV Infection ... 16

1.3. Hepatitis B Virus ... 17

1.3.1. Molecular Organization and Viral Proteins ... 17

1.3.2. HBV Replication Cycle ... 18

1.4. Categories of HBV Infection ... 19

1.5. Hepadnaviral Family ... 23

1.5.1. Duck Hepatitis B Virus ... 23

1.5.2. Ground Squirrel Hepatitis Virus ... 24

1.5.3. Woodchuck Model of HBV infection ... 24

1.5.3.1. Woodchuck Hepatitis Virus ... 24

1.5.3.2. Categories of WHV Infection ... 25

1.6. Immune System Organization ... 27

1.6.1. Innate Immunity ... 29

1.6.1.1. Cells of the Innate Immune System ... 29

1.6.1.2. Pattern Recognition Receptors (PRRs) ... 29

1.6.2. Adaptive Immunity ... 30

1.6.2.1. Humoral Immune Response ... 30

1.6.2.2. T Cell-Mediated Immune Response ... 31

1.7. Toll-like Receptors ... 32

1.7.1. Background ... 32

1.7.2. Structure and Cellular Localization ... 33

1.7.3. Ligand Recognition ... 34

1.7.3.1. Extracellular TLRs ... 34

1.7.3.1.1. TLR1, 2 and 6 ... 34

1.7.3.1.2. TLR4 ... 35

1.7.3.1.3. TLR5 ... 36

1.7.3.1.4. TLR10 ... 36

1.7.3.2. Intracellular TLRs ... 37

v

1.7.3.2.1. TLR3 ... 37

1.7.3.2.2. TLR7 and 8 ... 38

1.7.3.2.3. TLR9 ... 38

1.7.3.2.4. TLR11 and 12 ... 39

1.7.3.2.5. TLR13 ... 40

1.7.4. TLR Signaling ... 40

1.8. TLRs and Antiviral Immunity ... 41

1.8.1. TLRs and Hepadnaviruses ... 42

1.8.2. Targeting TLRs in HBV Antiviral Therapy ... 45

1.8.3. TLRs as Vaccine Adjuvants ... 46

1.9. TLRs and the Woodchuck Model of HBV Infection ... 48

1.10. Objectives ... 49

Chapter 2 - Methods and Materials ... 51

2.1. Collection of Woodchuck Tissue Samples ... 51

2.1.1. Liver Biopsies ... 51

2.1.2. Autopsy Liver and Spleen Tissues ... 51

2.1.3. Preparation of Primary Hepatocytes and PBMCs ... 52

2.2. RNA Extraction ... 52

2.2.1. DNase Treatment of RNA ... 53

2.2.2. RNA Concentration, Purity, and Integrity Assessment ... 53

2.3. Reverse Transcription (RT) of RNA ... 55

2.4. Sense and Anti-Sense Primer Design for Detection of Woodchuck TLRs ... 55

2.5. End-Point PCR Conditions for Initial Amplification of Woodchuck TLRs ... 56

2.5.1. Agarose Gel Electrophoresis ... 58

2.6. Plasmid Construction ... 58

2.6.1. DNA Purification from Agarose Gel ... 58

2.6.2. Cloning of Purified TLR DNA Fragments ... 59

2.6.3. Mini-scale Preparations of Plasmid DNA ... 59

2.6.4. Restriction Enzyme Digestion of Miniprep ... 60

2.6.5. Automated DNA Sequencing ... 60

2.6.6. Maxi-scale Preparation of Plasmid DNA ... 61

2.7. Real-Time RT-qPCR for Quantification of Woodchuck TLRs ... 62

2.7.1. Primer Optimization ... 62

2.7.2. Determination of Sensitivity of Detection ... 63

2.7.3. Absolute Quantification ... 63

2.8. Real Time RT-qPCR for Quantification of Expression of Individual Woodchuck TLRs ... 65

2.8.1. Plate Layout and Controls ... 65

2.9. Multiplex Real-Time RT-qPCR for Simultaneous Quantification of Woodchuck TLRs1-10 ... 68

vi

2.9.1. Plate Layout and Controls ... 68

2.10. Animals and Categories of WHV Infection ... 71

2.10.1. Categories of WHV Infection ... 71

2.10.2. Animals and Samples Examined ... 72

2.11. Calculation of Relative Expression ... 74

2.12. Statistical analyses ... 74

Chapter 3 - Results ... 75

3.1. General Study Design ... 75

3.2. Woodchuck TLR1-10 Gene Fragment Identification and Their Sequence Confirmation ... 76

3.3. Optimization of Real-time RT-qPCR Conditions for Absolute Quantification of Woodchuck TLRs1-10 ... 108

3.3.1. Primer Specificity ... 108

3.3.2. Quantification Standard Curve Optimization ... 115

3.4. Housekeeping Gene Expression Profiles in Liver, Hepatocytes and PBMCs from Healthy and WHV-Infected Woodchucks ... 116

3.5. TLR Expression Levels in Normal Woodchuck Livers, Hepatocytes and PBMCs ... 119

3.6. Transcription of Individual TLRs in Livers and Hepatocytes Isolated from These Livers of Healthy Woodchucks and Animals with Different Stages of WHV Infection ... 119

3.7. Expression Profiles of TLRs1-10 in Sequential Liver Biopsies Obtained Prior to and During WHV Infection ... 125

3.8. Expression of TLRs1-10 in Sequential PBMC Samples of Healthy Animals and Those with Different Stages of Experimental WHV Infection ... 129

Chapter 4 - Discussion ... 132

4.1. Summary of Findings ... 132

4.2. Timeline of Woodchuck TLRs1-10 Identification ... 133

4.3. Woodchuck TLR1-10 mRNA Protein Coding Sequence Compatibility with Human TLRs1-10 ... 134

4.4. Amplification Techniques Utilized in This Study ... 135

4.5. TLRs1-10 Expression Profiles in Normal Woodchuck Livers and Isolated Hepatocytes Were Comparable, While PBMCs Displayed Different Patterns of TLRs1- 10 Expression than in Hepatic Tissue ... 137

4.6. There Are Significant Differences in TLR Expression Profiles in the Liver and Isolated Hepatocytes During the Course of WHV Infection ... 138

4.7. Selective TLRs are Upregulated in PBMCs Isolated from Woodchucks with CH ... 142

Chapter 5 – Conclusions and Significance ... 145

vii

5.1. Summary and Conclusions ... 145

5.1.1. Comments ... 148

5.2. Significance of Findings ... 149

Chapter 6 – Future Directions ... 150

References Cited ... 151

Appendices ... 167

viii List of Tables

Table 2.1. Oligonucleotide Primer Sequences and PCR Conditions Used for Initial

Amplification of Woodchuck TLRs1-10 ... 57 Table 2.2. Woodchuck TLR-Specific and Housekeeping Primer Sequences Used for

Expression Analysis of Woodchuck TLRs1-10 by Real-Time RT-qPCR ... 64 Table 2.3. Woodchuck Samples from Different Categories of WHV Infection Used in

This Study ... 73

ix

List of Figures

Figure 2.1. Plate layout for RT-qPCR quantification of individual TLRs in woodchuck samples. ... 66 Figure 2.2. Plate layout for multiplex RT-qPCR quantification of woodchuck TLRs1-10.

... 69 Figure 3.1. Initial PCR amplification of woodchuck-specific TLR1, analysis of minipreps

of TLR1 plasmid DNA, and sequence confirmation. ... 77 Figure 3.2. Initial PCR amplification of woodchuck-specific TLR2, analysis of minipreps

of TLR2 plasmid DNA, and sequence confirmation. ... 80 Figure 3.3. Initial PCR amplification of woodchuck-specific TLR3, analysis of minipreps

of TLR3 plasmid DNA, and sequence confirmation. ... 83 Figure 3.4. Initial PCR amplification of woodchuck-specific TLR4, analysis of minipreps

of TLR4 plasmid DNA, and sequence confirmation. ... 86 Figure 3.5. Initial PCR amplification of woodchuck-specific TLR5, analysis of minipreps

of TLR5 plasmid DNA, and sequence confirmation. ... 89 Figure 3.6. Initial PCR amplification of woodchuck-specific TLR6, analysis of minipreps

of TLR6 plasmid DNA, and sequence confirmation. ... 92 Figure 3.7. Initial PCR amplification of woodchuck-specific TLR7, analysis of minipreps

of TLR7 plasmid DNA, and sequence confirmation. ... 95 Figure 3.8. Initial PCR amplification of woodchuck-specific TLR8, analysis of minipreps

of TLR8 plasmid DNA, and sequence confirmation. ... 98 Figure 3.9. Initial PCR amplification of woodchuck-specific TLR9, analysis of minipreps

of TLR9 plasmid DNA, and sequence confirmation. ... 101 Figure 3.10. Initial PCR amplification of woodchuck-specific TLR10, analysis of

minipreps of TLR10 plasmid DNA, and sequence confirmation. ... 104 Figure 3.11. An example of real-time RT-qPCR optimization and determination of the

assay sensitivity for detection of woodchuck TLR4. ... 109

x

Figure 3.12. An example of real-time RT-qPCR optimization and determination of the assay sensitivity for detection of woodchuck TLR10. ... 112 Figure 3.13. HPRT is a more reliable housekeeping gene than b-actin when comparing

gene expression in woodchuck livers and hepatocytes derived from these livers. 117 Figure 3.14. Baseline expression levels of TLRs1-10 in healthy woodchuck livers,

hepatocytes and PBMCs. ... 120 Figure 3.15. TLRs1-10 expression profiles in livers and hepatocytes purified from these

livers from healthy and WHV-infected woodchucks ... 123 Figure 3.16. Transcription levels of TLRs1-10 in sequential liver biopsy samples

collected from woodchucks with different forms of WHV infection. ... 126 Figure 3.17. Profiles of TLRs1-10 expression in sequential PBMC Samples isolated

from heathy woodchucks and those with different forms of WHV infection. ... 130

xi

List of Abbreviations AFL Acute liver failure

AH Acute hepatitis

ALT Alanine aminotransferase

Anti-HBc Antibodies to hepatitis B virus core antigen Anti-HBe Antibodies to hepatitis B virus e antigen

Anti-HBs Antibodies to hepatitis B virus surface antigen

Anti-WHc Antibodies to woodchuck hepatitis virus core antigen Anti-WHs Antibodies to woodchuck hepatitis virus surface antigen AP1 Activator protein 1

APC Antigen presenting cell ASGPR Asialoglycoprotein receptor ASHV Artic squirrel hepatitis virus AST Aspartate aminotransferase

AT Adenine-thymine nucleotides

BCR B cell receptors

BHBV Bat hepatitis B virus

BLAST Basic local alignment search tool

bp Base pair

cccDNA Covalently closed circular deoxyribonucleic acid CD Cluster of differentiation

CD21 Cluster of differentiation molecule 21 cDNA Complimentary deoxyribonucleic acid

CH Chronic hepatitis

CHB Chronic hepatitis B CLR C-type lectin receptor

CpG Cytosine-phosphate-guanine motif

CREB Cyclic AMP-responsive element binding protein CTL Cytotoxic T lymphocyte

DC Dendritic cell

ddd Double-distilled, deionized DEPC Diethyl pyrocarbonate DHBV Duck hepatitis B virus

DMSO Dimethyl sulfoxide

dNTP Deoxynucleotide triphosphate

dpi Days post-infection

DTT Dithiothreitol

EB Ethidium bromide

ESCRT Endosomal sorting complexes required for transport

ETV Entecavir

FCS Fetal calf serum

GC Guanine-cytosine nucleotides

GSHV Ground squirrel hepatitis virus

GTE Glucose-Tris-ethylenediaminetetraacetic acid HBcAg Hepatitis B core antigen

xii HBeAg Hepatitis B e antigen HBsAg Hepatitis B surface antigen HBV Hepatitis B virus

HBx Hepatitis B X protein HCC Hepatocellular carcinoma HHBV Heron hepatitis B virus

HIV Human immunodeficiency virus

HPRT Hypoxanthine-guanine phosphoribosyltransferase HSP Heat shock protein

HSV Herpes simplex virus

IC Internal control

IFN Interferon

IFN-α Interferon alpha IFN-β Interferon beta IFN-γ Interferon gamma IFN-λ Interferon lambda IL-1R Interleukin 1 receptor

IRAK Interleukin 1 receptor-associated kinase IRF Interferon regulatory factor

ISS Immunostimulatory sequence JNK JUN N-terminal kinase

Kb Kilobase

LB Luria-Bertani medium

LBP Lipopolysaccharide binding protein

LMP Low-melting point

LPS Lipopolysaccharides

LRR Leucine-rich repeat LTA Lipoteichoic acid

M-MLV Moloney murine leukemia virus

MAL/TIRAP MyD88-adaptor like/TIR-associated protein MAPK Mitogen-associated protein kinase

MCMV Murine cytomegalovirus MD-2 Lymphocyte antigen 96

MHC Major histocompatibility complex MPLA Monophosphoryl lipid A

mRNA Messenger RNA

MyD88 Myeloid differentiation primary response protein (88)

NaOH Sodium hydroxide

NCBI National Center for Biotechnology Information

NF-kB Nuclear factor kappa-light-chain-enhancer activated B cells

NK Natural killer cell

NKT Natural killer T cell

NLR NOD-like receptor

NTC No template control

NTCP Sodium taurocholate cotransporting polypeptide OBI Occult hepatitis B virus infection

xiii

ODN Oligonucleotide

ORF Open reading frame

PAMP Pathogen-associated molecular patterns PBMC Peripheral blood mononuclear cells PCR Polymerase chain reaction

PD-1 Programmed cell death protein 1 PD-L1 Programmed cell death ligand 1 pDC Plasmacytoid dendritic cell

pg Pregenomic

POI Primary occult infection

poly (I:C) Polyinoscinic-polycytidylic acid PreAH Pre-acute hepatitis

PRR Pattern recognition receptor PWH Primary woodchuck hepatocyte

RC Relaxed circular

RIN RNA integrity number RLR RIG-I-like receptor

RNA Ribonucleic acid

rpm Revolutions per minute

rRNA Ribosomal RNA

RT Reverse transcription

RT-PCR Reverse transcription polymerase chain reaction

RT-qPCR Quantitative reverse transcription polymerase chain reaction SDH Sorbitol dehydrogenase

SDS Sodium dodecyl sulfate SLAH Self-limited acute hepatitis

SOC Super optimal broth with catabolite repression SOI Secondary occult infection

TAE Tris-acetate-ethylenediaminetetraacetic acid TE Tris-ethylenediaminetetraacetic acid

Th T helper cell

TIR Toll-interleukin 1 receptor TLR Toll-like receptor

TNF Tumor necrosis factor TNF-α Tumor necrosis factor alpha

TRAF Tumor necrosis factor receptor-associated factor TRAM Toll-receptor-associated molecule

TRIF Toll-receptor-associated activator of interferon VSV Vesicular stomatitis virus

WHcAg Woodchuck hepatitis virus core antigen WHeAg Woodchuck hepatitis virus e antigen WHO World Health Organization

WHsAg Woodchuck hepatitis virus surface antigen WHV Woodchuck hepatitis virus

WMHBV Woolly monkey hepatitis B virus β-Actin Beta-actin

xiv

List of Appendices

Figure A1. Expression levels of TLRs1-10 in sequential liver biopsy samples and PBMCs during the course of hepadnaviral infection in woodchuck #1 that

progressed from acute hepatitis (AH) to chronic hepatitis (CH). ... 167 Figure A2. Expression levels of TLRs1-10 in sequential liver biopsy samples and

PBMCs during the course of hepadnaviral infection in woodchuck #2 that

progressed from acute hepatitis (AH) to chronic hepatitis (CH). ... 170 Table A1. GenBank Accession Numbers of Woodchuck TLR1-10 Partial Gene

Sequences Identified in This Study ... 173 Table A2. Copy Number Values for the Housekeeping Gene HPRT and TLRs1-10 in

Woodchuck Livers Investigated in This Study ... 174 Table A3. Copy Number Values for the Housekeeping Gene HPRT and TLRs1-10 in

Woodchuck Hepatocytes Investigated in This Study ... 175 Table A4. Copy Number Values for the Housekeeping Gene HPRT and TLRs1-10 in

Woodchuck PBMCs Investigated in This Study ... 176

15 Chapter 1 – Introduction

1.1. Brief History of Studies on Hepatitis B Virus Identification

Virus-induced hepatitis is an inflammatory liver disease caused by DNA or RNA viruses that have a specific affinity for the liver, also known as hepatotrophic viruses.

The hepatitis B virus (HBV) is the largest causative agent of viral hepatitis in the world and is characterized by both its hepatotrophic and lymphotrophic nature. In the 1940’s, the name “hepatitis B” was first introduced in order to categorize an infectious liver disease that was mainly transmitted by exposure to contaminated blood (MacCallum, 1946). It was not until 1965 when Dr. Baruch Blumberg discovered HBV envelope lipoprotein, then named the Australian antigen, in the blood of an Australian aboriginal (Blumberg et al., 1965). Following further research, it was determined that the Australian antigen, now referred to as the hepatitis B surface antigen (HBsAg), was indicative of active HBV infection. In the 1970’s, Dr. David Dane discovered viral particles with a diameter of 42-nm, known as Dane particles, that were eventually identified to be HBV virions (Dane et al., 1970). Since the identification of HBsAg and the HBV virion, subsequent immunological and molecular analysis has led to the identification of HBV associated proteins and the sequencing of the entire HBV genome.

Vaccine development began with Dr. Blumberg’s early work, however, it was not until 1986 that a yeast-derived HBsAg vaccine became the standard vaccine against HBV (Gerlich, 2013). Currently, several recombinant HBV vaccines containing the major protein of HBsAg, named the S (small) protein, are available to generate protection against HBV (Lavanchy, 2012).

16 1.2. Epidemiology of HBV Infection

According to the World Health Organization (WHO), an estimated 240 million people worldwide are affected by chronic, serum HBsAg-positive, hepatitis B (CHB) and approximately one million persons die each year due to complications caused by HBV infection (World Health Organization, 2016). It is estimated that another 2 billion people may have occult HBV infection without showing any clinical symptoms. Furthermore, prophylactic vaccines that are available do not inhibit transmission of HBV from infected mothers to their babies, which is currently the main route of virus spread. In consequence, severe liver cirrhosis and liver cancer, called primary hepatocellular carcinoma (HCC), caused by the virus will remain a significant health problem for many decades to come. The rate of HBV infection varies depending on geographical region and is generally highest in developing countries. These countries are suffering from political and socio-economic problems that make it difficult to manage the prevention and treatment of the disease (Zampino et al., 2015). HBV is highly endemic in regions such as South East Asia, China, sub-Saharan Africa, the Amazon Basin, and Northern Canada, where an estimated 8% of the population are chronic HBsAg-positive carriers (Hou et al., 2005). In these areas, HBV is most commonly acquired during childhood, either through perinatal transmission (mother to child) or through horizontal transmission (individual to individual). Intermediate rates of endemicity are found in areas such as Eastern and Southern Europe, the Middle East, Japan and South America. It is estimated that 2-7% of individuals in these areas are chronically infected.

In developed areas of the world, including North America, Northern and Western Europe and Australia, less than 1% of the population have CHB. The number of

17

countries that included HBV immunization in their national vaccination schedule has constantly increased since the WHO’s recommendations in 1992 (Schweitzer et al., 2015). However, immunization and proper disease management are still lacking in many countries, therefore, chronic HBV infection remains a very serious health problem in many regions of the world.

1.3. Hepatitis B Virus

1.3.1. Molecular Organization and Viral Proteins

HBV is the prototypic member of the Hepadnaviridae family. Hepadnaviruses have small genomes formed by partially double-stranded and partially single-stranded DNA, referred to as relaxed circular (RC) DNA. HBV has a circular genome that is 3.2 kilobases (Kb) in length, consisting of a full length minus strand DNA and an incomplete plus strand DNA. The minus strand contains the entire coding information for the virus and its circularity is maintained by short cohesive overlapping regions at the 5’-ends of the plus and minus strands. The HBV genome is organized into four open reading frames (ORFs). These include the envelope or surface (S), core (C), polymerase (P), and X ORFs (Locarnini and Zoulim, 2010). In total, the HBV genome codes for 7 proteins, including pre-core, core, polymerase, X (HBx) and three surface or envelope proteins. The S ORF codes for the three envelope proteins, the large (preS1), the middle (preS2) and the small (S). They share a common C-terminus but differ at the N- terminus. All three proteins are glycosylated, type II transmembrane proteins that make up the components of the 22-nm-diameter noninfectious particles, also known as HBsAg (Seeger and Mason, 2000). The C ORF encodes the viral capsid protein, also

18

referred to as nucleocapsid or hepatitis B core antigen (HBcAg). In addition to HBcAg, the C ORF encodes the pre-core protein. The pre-core protein is essentially the core protein with an N-terminal signal peptide that gets proteolytically processed and secreted from infected cells. The secreted protein is known as hepatitis B e antigen (HBeAg) and its role has not yet been clearly elucidated (Seeger and Mason, 2015).

The P ORF codes for virus polymerase and comprises nearly 80% of the hepadnaviral genome. The enzyme exhibits both DNA polymerase and RNA polymerase (reverse transcriptase) activity, and is critical to the replication of the HBV genome through a pregenomic (pg) RNA template. Lastly, the X ORF encodes the HBx protein and its role in the viral infection lifecycle is not well determined. It has been shown to regulate viral replication, as well as numerous host cellular processes, through transcriptional activation of both viral and host genes. It has also been implicated in the development of HCC (Tang et al., 2006).

1.3.2. HBV Replication Cycle

The first stage of HBV infection begins with attachment of the viral particle to its target cell. The specific receptor responsible for viral attachment and entry has recently been identified as sodium taurocholate cotransporting polypeptide (NTCP) (Yan et al., 2012). Studies have shown that the preS1 domain of the HBV envelope is required for initiation of infection and it specifically binds to the NTCP receptor (Yan et al., 2014;

Slijepcevic et al., 2015; Sankhyan et al., 2016). After attachment, the viral envelope is shed and the core particle containing virus genome material is actively transported to the nucleus. In the nucleus, the genomic RC DNA is released from the nucleocapsid of

19

the virus and converted to covalently closed circular DNA (cccDNA) by the host’s DNA cellular repair enzymes. The detection of cccDNA provides definitive proof of HBV replication. From the cccDNA, the cell’s RNA polymerase II generates pgRNA from which core protein and DNA polymerase are translated (Gerlich, 2013). The pgRNA is then packaged within the core proteins of the virus, along with DNA polymerase, where it serves as the transcriptional template for the minus-strand DNA. The plus-strand DNA is then transcribed from the minus-strand, followed by simultaneous degradation of the pgRNA. Once the RC DNA is produced, the mature nucleocapsid particles can follow two pathways. They can re-enter the nucleus and contribute to another round of replication or be packaged into virions and released from the cell. Similar to other enveloped viruses, HBV uses the cellular endosomal sorting complexes required for transport (ESCRT) to release virions from the infected cell (Blondot et al., 2016).

1.4. Categories of HBV Infection

HBV causes acute and chronic liver disease, liver cirrhosis, as well as HCC.

More specifically, HBV is a non-cytopathic virus that causes tissue damage by inducing virus-specific immune responses. Due to infection, hepatocytes present viral epitopes complexed with major histocompatibility complex (MHC) class I molecules on their plasma membrane. This complex is recognized by cytotoxic T lymphocytes (CTLs) that target the cells for destruction. The clinical course of HBV infection varies between individuals and can lead to a wide spectrum of liver disease. Generally, infection with HBV can be divided in several categories, including acute hepatitis (AH), fulminant hepatitis, chronic hepatitis (CH), and occult HBV infection (OBI).

20

AH type B is usually diagnosed in patients anywhere from 1-6 months following exposure to the virus. AH is defined by the appearance of HBsAg in the serum. About 70% of patients with AH do not have clinical symptoms and the infection can go undetected (Liang, 2009). About 30% of adults with AH develop clinical symptoms that can range from mild fever, anorexia and nausea to more severe symptoms, including jaundice. Fulminant hepatitis, also known as acute liver failure (AFL), occurs in less than 1% of patients and is characterized by severe liver injury with necrosis, loss of liver function, and frequent death (Gotthardt et al., 2007). Eventually, individuals with AH will clear HBsAg within 6 months from its appearance and develop antibodies to HBsAg (anti-HBs). AH diagnosis can be supported by the presence of other HBV serological markers, such as HBeAg, antibodies to HBcAg (anti-HBc) and HBeAg (anti-HBe), molecular markers (HBV DNA) and the increase in liver enzymes (i.e., alanine aminotransferase [ALT] and aspartate aminotransferase [AST]). Persistence of HBsAg in circulation for longer than 6 months is recognized as a marker of the development of CHB.

Early CHB is characterized by the serological presence of serum HBsAg, HBeAg, anti-HBc antibodies and HBV DNA, along with the detection of HBV DNA, mRNA, and cccDNA in liver tissue that are indicative of active viral replication. Around 5-10% of adults who become infected with HBV will develop CHB, while the remaining individuals will resolve the infection and establish life-long, usually asymptomatic OBI that can be reactivated when the patient becomes immunocompromised. In contrast, about 90% of neonates who acquire HBV by perinatal transfer (transmission from mother to child) will develop CHB (Schillie et al., 2015). In both situations, the immunological profile of CHB

21

can be categorized into three phases: immune tolerant, immune active and immune inactive.

Immune tolerant CHB occurs almost exclusively in neonates who acquire the infection at birth from their HBV-infected mothers. This phase of CHB is characterized by the presence of HBeAg, normal liver aminotransferases, high levels of serum HBV DNA (>100,000 copies/mL) and minimal to absent liver inflammation (McMahon, 2008).

The immune tolerant phase can last for up to 30 years with little disease progression due to the absence of a CTL response (Hui et al., 2007). However, following the immune tolerant phase, almost all individuals will enter the immune active phase during early adolescence or young adulthood. As previously indicated, about 5-10% of individuals who become infected as an adult will develop CHB and will experience the immune active phase in the early stages of CHB.

The immune active phase of CHB is characterized by the presence of HBeAg and HBV DNA (>10,000 copies/mL) in the serum, an increase in serum ALT levels, and histologically evident active liver inflammation (McMahon, 2008). Individuals will remain HBeAg-positive or can seroconvert to the HBeAg-negative stage with subsequent development of anti-HBe antibodies. In any case, these individuals are at highest risk of liver disease complications, such as cirrhosis and development of HCC. Following immune active CHB, some individuals can enter the immune inactive stage. This is defined by a reduction in HBV DNA (<10,000 copies/mL), normal serum ALT, and a decline of active liver disease (McMahon, 2008). However, reactivation can occur spontaneously and HBV infection in all phases should be monitored closely. Over time,

22

CHB can lead to liver fibrosis and cirrhosis, and the risk of HCC is 100-times greater than in healthy individuals (Busch and Thimme, 2015).

More recently, another category of HBV infection has been identified in which HBsAg is apparently cleared from the individual, however, the HBV genome and low level replication are still detectable. OBI is characterized by undetectable serum HBsAg by current clinical assays, while HBV DNA persists at the level of <100-200 copies/mL in the liver and/or lymphatic tissue (Michalak et al., 1994; Michalak, 2000). Resolution of AH and the appearance of anti-HBs was thought to signify clearance of the virus, however, this is not the case (Raimondo et al., 2008a; Raimondo et al., 2008b). This was also clearly documented in the woodchuck model of hepatitis B (Michalak et al., 1999). Furthermore, perinatal transmission of infectious hepadnavirus was demonstrated in offspring born to woodchuck mothers that had resolved AH (Coffin and Michalak, 1999). In humans, the mechanisms of OBI infection are not completely understood. More recently, HBV DNA and HBsAg detection techniques have become more sensitive, allowing for more reliable diagnosis of OBI. In the woodchuck model of HBV infection, it has been shown that OBI is accompanied by intermittent liver inflammation and may lead to the development of HCC. Two distinct forms of OBI have been documented to occur in woodchucks and humans (i.e., secondary [SOI] and primary occult infection [POI]) (Michalak et al., 2004; Zerbini et al., 2008; Mulrooney- Cousins et al., 2014).

23 1.5. Hepadnaviral Family

The hepadnaviral family is subdivided into two genera: Orthohepadnaviridae (mammalian viruses) and Avihepadnaviridae (avian viruses). All viruses from this family share unique structural, molecular and biological features. All hepadnaviruses have virions that are between 40-48-nm in diameter, and are spherical in shape. The genomes of these viruses are composed of partially double-stranded RC DNA that can range from 3.0-3.3 Kb in length. Replication strategies are similar, involving polymerase and reverse transcriptase activity, along with the excess production of subviral particles exclusively composed of envelope proteins and lipids (Dandri et al., 2005).

Since the discovery of HBV, there have been several hepadnaviral infections identified in both avian and mammalian hosts. These include the woodchuck hepatitis virus (WHV), ground squirrel hepatitis virus (GSHV), artic squirrel hepatitis virus (ASHV), duck hepatitis B virus (DHBV), heron hepatitis B virus (HHBV), woolly monkey hepatitis B virus (WMHBV) and more recently the bat hepatitis B virus (

BHBV

1.5.1. Duck Hepatitis B Virus

DHBV is a prototypic member of the avian hepadnaviral family. Although the DHBV has been proven to be a useful animal model for HBV infection, there are major differences between avian hepadnaviruses when compared to their mammalian counterpart. Firstly, avian viral genomes are smaller than mammalian viral genomes and share less nucleotide sequence homology with HBV. The DHBV genome lacks the

24

X ORF and only encodes two envelope proteins, instead of three (Dandri et al., 2005).

In the past, studies that have utilized the DHBV have helped to elucidate the mechanisms of hepadnaviral replication. However, DHBV is not a good model of liver inflammation and HCC, as infection usually results in a very mild liver pathology and HCC develops in the context of exposure to alphatoxins (Cova et al., 1993).

1.5.2. Ground Squirrel Hepatitis Virus

GSHV is a mammalian member of the hepadnaviral family. GSHV was the second HBV-related virus discovered in non-primate animals and was originally identified in the Beechy ground squirrel in 1979. Its virion is 47-nm in diameter, which is slightly larger than that of HBV (Marion et al., 1980). GSHV was mainly used to elucidate the mechanism of hepadnaviral replication and was found to cause hepatitis and HCC (Minuk et al., 1986; Enders et al., 1987). Interestingly, GSHV is infectious to woodchucks and can eventually lead to HCC in some animals. Nevertheless, HCC development, when compared to WHV-infected woodchucks, is much slower in GSHV- infected woodchucks (Seeger et al., 1991).

1.5.3. Woodchuck Model of HBV infection

1.5.3.1. Woodchuck Hepatitis Virus

WHV was first discovered in a colony of woodchucks (Marmota monax) that exhibited hepatitis and HCC at the Philadelphia Zoological Garden (Summers et al., 1978). Since its discovery, studies have shown that WHV has significant molecular and pathogenic similarities to HBV. With time it became apparent that woodchucks infected

25

with WHV represent the closest natural model of human HBV infection. Both HBV and WHV genome size is almost identical (~3.2 Kb and ~3.3 Kb in length, respectively), while their nucleotide sequence homology is anywhere from 62% to 72% (Mulrooney- Cousins and Michalak, 2015). This high homology translates to a high degree of antigenic cross-reactivity between HBV and WHV envelope and core proteins. Like HBV, the WHV virion, at 45-nm in diameter, consists of an exterior envelope protein (WHV surface antigen [WHsAg]) and an inner nucleocapsid (WHV core antigen [WHcAg]) containing the WHV genome. Furthermore, replication strategy, viral proteins and tropism towards hepatocytes and immune cells are almost identical to HBV (Menne and Cote, 2007; Mulrooney-Cousins and Michalak, 2015).

1.5.3.2. Categories of WHV Infection

Progression and outcomes of WHV infection in woodchucks are very similar to HBV infection in humans. In both infections, liver involvement begins with AH and can advance to CH and eventually HCC. Excluding the apparent lack of liver cirrhosis in woodchucks, histological features of liver inflammation are comparable to HBV infection (Hodgson and Michalak, 2001). Following exposure to WHV, the AH stage of infection normally becomes evident with the detection of WHsAg in the serum and liver injury through detection of biochemical indicators (i.e., sorbitol dehydrogenase [SDH] and ALT). Undetectable WHsAg prior to 6 months post-infection denotes spontaneously resolution of AH and the animal is designated to have self-limited acute hepatitis (SLAH). Approximately 90% of adult woodchucks will resolve AH, however, residual amounts of replicating WHV remains detectable in the liver and the lymphatic system to

26

the end of life (Michalak et al., 1999; Menne and Cote, 2007). Even with resolution of hepatitis, these woodchucks still have a lifetime risk of about 20% for the development of HCC. If WHsAg persists in circulation for longer than 6 months, CH is diagnosed.

Comparable to humans, CH infection occurs in about 5-10% of woodchucks who acquire the infection as an adult, while roughly 60-75% of woodchucks with perinatally acquired WHV infection progress to chronicity (Cote et al., 2000). A major difference between HBV and WHV CH is that the development of HCC in woodchucks occurs at much higher rate (80%-90%) than in humans with CH type B (~5%)(Popper et al., 1981;

Korba et al., 1989; Mulrooney-Cousins and Michalak, 2015). Due to the development of highly sensitive nucleic acid detection assays, occult WHV infection is being recognized for its involvement in the development of cryptogenic HCC (Mulrooney-Cousins et al., 2014; Mulrooney-Cousins and Michalak, 2015).

The presence of HBV DNA or WHV DNA with the absence of identifiable HBsAg or WHsAg, is defined as an occult infection. Two forms of occult infection have been identified in WHV-infected woodchucks, SOI and POI. First to be identified, SOI is characterized by low levels of WHV DNA, the presence of antibodies against WHV core antigen (anti-WHc), and residual liver inflammation after resolution of AH (Michalak et al., 1999). Furthermore, animals with SOI have detectable WHV DNA in their lymphatic system which may contribute to the lifelong maintenance of the virus. It has been demonstrated that WHV is transmissible from SOI mothers to their offspring without evident serological markers of infection but detectable WHV DNA in both serum and lymphatic system (Coffin and Michalak, 1999). This observation provoked further studies investigating the transmission of low level WHV-infection. It was found that

27

WHV from these offspring could be serially transmitted between adult immunocompetent hosts and induce serologically silent but molecularly evident, asymptomatic infection, referred to as POI (Michalak et al., 2004). Additionally, animals experimentally infected with WHV doses of less than 1000 virions develop POI. POI is characterized by the absence of classical serological markers of WHV infection, such as serum WHsAg, anti-WHc and anti-WHs antibodies, however, viral DNA is detectable in the plasma and the immune system. Over time, POI can spread to the liver without induction of hepatitis, but HCC develops in about 20% of the animals (Mulrooney- Cousins and Michalak, 2007; Mulrooney-Cousins and Michalak, 2015). The woodchuck model of OBI can be used to advance our understanding of occult infection in humans, including mechanisms of reactivation of asymptomatic infection, clinically unapparent viral transmission, and its potential role in the development of cryptogenic HCC.

1.6. Immune System Organization

The mammalian immune system is made up of a network of cells, tissues and organs that work in concert to protect against invading pathogens through recognition of self and non-self. To elicit a response to a foreign agent, the body has evolved several mechanisms to evade or destroy the potentially harmful pathogen. The first line of defense in mammals is a non-specific immune response, referred to as innate immunity.

The innate immune system includes all anatomical barriers, as well as certain cells and soluble factors that are strategically located in the body. Infection of host cells leads to the initiation of the innate immune responses, resulting in the induction and expression of type I interferons (IFNs) (i.e., IFN-α and IFN-β), type III IFNs (i.e., IFN-λ) and pro-

28

inflammatory cytokines (Ank et al., 2008; Bowie and Unterholzner, 2008; Egli et al., 2014). Upon recognition of a pathogen, the innate immune response is nonspecific and generalized. In the event that the infectious agent persists, the body has evolved a more specific immune response that is tailored towards a particular antigen, known as adaptive immunity.

The adaptive side of the immune response relies on antigen-specific receptors expressed by lymphocytes, T and B cells, that are capable of recognizing and selectively eliminating pathogens. Generally speaking, T lymphocytes are involved in pathogen elimination through direct binding and cytokine secretion, while B lymphocytes rely on the production of antigen-specific neutralizing antibodies. These cells possess membrane bound and soluble proteins that have high specificity towards antigenic sites on foreign microorganisms and molecules. The adaptive immune system is able to recognize millions of antigens and is highly specific due to the rearrangement of immunoglobulin and T cell receptor genes that produce an immense number of antigen- specific receptor combinations. Unlike the innate immune system, which relies primarily on phagocytic cells and antigen presenting cells (APCs), the adaptive immune response relies on clonal gene rearrangement to form a large repertoire of antigen-specific T and B cells (Mogensen, 2009). Historically, management of the adaptive immune response was the focus of treatments for infectious diseases and cancers. However, the therapeutic importance of innate immunity has been recently recognized in the context of several infection models.

29 1.6.1. Innate Immunity

1.6.1.1. Cells of the Innate Immune System

Innate immune cell subsets include dendritic cells (DCs), monocytes/macrophages, granulocytes (neutrophils, eosinophils, basophils), mast cells, natural killer (NK) and natural killer T (NKT) cells. Each cell type possesses unique receptors that are able to detect and initiate downstream signaling which may mediate further innate immune responses or help activate the adaptive immune system.

Furthermore, innate immune cells release soluble molecules, such as complement, antimicrobial peptides and cytokines that detect and initiate immune clearance thorough phagocytosis, apoptosis or necrosis (Kumar et al., 2013).

1.6.1.2. Pattern Recognition Receptors (PRRs)

The first step in the initiation of the innate immune response against microbial pathogens involves sensing of pathogen-associated molecular patterns (PAMPs) through use of PRRs that are expressed on the plasma membrane and in the cytoplasm of innate immune cells. Recognition of a pathogen initiates a series of signaling events that results in the production of pro-inflammatory cytokines, including type I IFNs, chemokines and antimicrobial peptides. In addition to eliminating early infection, activation of PRRs and the release of IFNs help initiate the adaptive immune response by priming T helper (Th) cells and CTLs (Bowie and Unterholzner, 2008). PRRs have evolved to recognize a wide range of microbial PAMPs and are expressed by a variety of innate immune cells, such as granulocytes, monocytes/macrophages and DCs.

30

PRRs include Toll-like receptors (TLRs), NOD-like receptors (NLRs), RIG-I-like receptors (RLRs), and C-type lectin receptors (CLRs) (Owen et al., 2013). PRRs can be classified based on their cellular localization as membrane-bound or intracellular.

Membrane-bound PRRs include TLRs and CLRs, while NLRs and RLRs are found intracellularly. PRRs cooperate to detect a wide variety of molecules from microbial pathogens, including bacterial carbohydrates (e.g., lipopolysaccharides [LPS]), bacterial peptides (e.g., flagellin), viral nucleic acids and proteins, and fungal glucans. PRRs play an important role in viral recognition and have been implicated in the pathogenesis of hepadnaviral infection. The main subject of this study is the identification of woodchuck TLRs and the delineation of their expression during the course of hepadnaviral infection in woodchucks. TLRs will be covered in detail in Section 1.7.

1.6.2. Adaptive Immunity

1.6.2.1. Humoral Immune Response

The adaptive immune response relies on antibody production by B cells to neutralize and clear invading pathogens. The diversity of antigen recognition is due to the combinatorial joining of variable (V), diversity (D) and joining (J) gene fragments which encode the antigen-binding regions of B cell receptors (BCRs) (Notarangelo et al., 2016). The large diversity of antigen recognition allows for the generation of a response that is specific for a particular pathogen or pathogen-infected cell. The most important aspect of humoral immunity is the generation of antibodies by memory B cells and plasma cells that have long lasting, high-affinity for a foreign agent. Clonal selection of B lymphocytes generally occurs through one of three mechanisms: T cell-

31

dependent activation, and type 1 or type 2 T cell-independent activation (Owen et al., 2013). T cell-dependent activation occurs when an antigen binds to the immunoglobulin receptor on a B cell and is internalized and presented to a Th cell. Subsequently, the Th

cell binds to the MHC class II-peptide antigen complex presented by the B cell and delivers activation signals through co-receptor interactions and cytokine production.

Conversely, type 1 T cell-independent activation occurs when an antigen binds to both an immunoglobulin receptor and an innate immune receptor (i.e., TLR) located on the B cell. While type 2 T cell-independent activation is taking place when the B cell recognizes an antigen that has already been identified and bound by complement proteins. In this case, crosslinking occurs when the B cell binds the antigen and complement proteins through immunoglobulin and cluster of differentiation (CD) molecule 21 (CD21) receptors (Vos et al., 2000). The resulting crosslink is sufficient to initiate an activation signal for B cell clonal expansion. Ultimately, activation and clonal expansion of plasma and memory B cells that express antigen-specific antibodies is vital to the development of a long-term humoral immune response.

1.6.2.2. T Cell-Mediated Immune Response

T lymphocytes play a critical role in the adaptive immune response and are largely divided in two groups: CD4+ T cells and CD8+ T cells. T cells are activated by professional APCs, typically DCs, that have engulfed a foreign pathogen and presented its associated peptides on MHC class I or MHC class II molecules on the cell surface.

Additionally, T cells can become activated when foreign peptides are recognized by circulating naive CD4+ or CD8+ T cells. Activation results in differentiation and clonal

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expansion into effector CD4+ and CD8+ T lymphocytes. Classically, CD4+ T cells, also referred to as Th cells, differentiate into either a type 1 (Th1) or type 2 (Th2) cell that are classified by the cytokines they secrete. More recently, additional Th cell subsets have been identified, including Th9, Th17, Th22, T follicular-helper (Tfh) and T-regulatory (Tregs) (Hirahara and Nakayama, 2016). In any case, Th cells can influence a variety of immune cells indirectly through the production of cytokines, resulting in an immune response that is catered to the type of infection. In contrast, CD8+ T cells, also referred to as CTLs, induce death of infected cells directly. When activated, CD8+ CTLs can recognize and destroy target cells through activation of the cell’s internal apoptotic cycle. Cells are targeted based on their expression of pathogenic peptides on MHC class I molecules. In addition to cell cytotoxicity, CTLs produce proinflammatory and antiviral cytokines (i.e., TNF-α and IFN-γ) to aid in immune clearance. Both CD4+ and CD8+ T cells can differentiate into memory T cells for long-lasting immune protection.

However, the exact mechanism and sequence of immunological events leading to the development of memory T cells is not completely understood (Gerritsen and Pandit, 2016).

1.7. Toll-like Receptors

1.7.1. Background

The name Toll-like receptor is derived from the Toll receptor originally identified in Drosophila that is required for dorsal-ventral patterning during development (Hashimoto et al., 1988). Investigation into Drosophila’s immune response to fungal agents implicated the Toll protein in the control of expression of the antifungal peptide

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gene drosomycin (Lemaitre et al., 1996). Due to the similarities between the cytoplasmic domains of Drosophila Toll and human interleukin-1 (IL-1) receptors, it was thought that both may be related to ancient evolutionary immune responses. This discovery ultimately led to the identification of a family of human TLR genes residing on chromosome 4 (TLRs 1, 2 and 3), chromosome 9 (TLR4), and chromosome 1 (TLR5) (Rock et al., 1998). Since their discovery, 13 TLRs have been identified. Genes encoding TLR1-11 are expressed by both human and mouse; however, mouse TLR10 is a pseudogene and human TLR11 contains a stop codon, resulting in no protein expression for these two TLR genes. While TLR12 and TLR13 are expressed in mouse, they are not expressed in humans (Broz and Monack, 2013; Yarovinsky, 2014).

1.7.2. Structure and Cellular Localization

TLRs are a family of type I transmembrane proteins characterized by an extracellular, horseshoe shaped, leucine-rich repeat (LRR) domain and a cytoplasmic domain referred to as the Toll/IL-1 receptor (TIR) domain (Owen et al., 2013). The cytoplasmic domain was given its name due to its similarities to the cytoplasmic domain of the mammalian IL-1 receptor (IL-1R). When the extracellular domain binds specific PAMPs, the intracellular domain alters its configuration causing the initiation of signaling events. These events include translocation of transcription factors into the nucleus, interferon-stimulated gene regulation, and cytokine modulation.

Diverse cell types have been found to express TLRs, such as airway and gut epithelial cells, endothelial cells, B cells, T cells, NK cells, macrophages, monocytes, DCs, neutrophils, basophils and mast cells (Pandey and Agrawal, 2006). In innate

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immune cells (i.e., macrophages and DCs), ligand recognition and binding is followed by a series of signaling events that result in an inflammatory response and release of antimicrobial agents. Activation of TLRs is a critical step in the development of antigen- specific adaptive immunity (Takeda and Akira, 2005). In B cells, TLRs have been implicated as important regulators of innate signals regulating adaptive immune responses (Hua and Hou, 2013). TLRs recognize a wide range of pathogens and, for the most part, can be categorized by their subcellular localization. Thus, TLR1, 2, 4-6 and 10 are located on the cell surface, while TLR3, 7-9 and 11-13 are located intracellularly. In general, extracellular TLRs are involved in the recognition of PAMPs composed of lipids and proteins, while intracellular TLRs recognize nucleic acid sequence motifs.

1.7.3. Ligand Recognition

1.7.3.1. Extracellular TLRs

1.7.3.1.1. TLR1, 2 and 6

TLR2 recognizes a wide range of PAMPs and is known as the most promiscuous TLR of the family. Ligands for TLR2 include lipoproteins from Gram-negative bacteria, mycoplasma and spirochetes, peptidoglycan and lipoteichoic acid (LTA) from Gram- positive bacteria, lipoarabinomannan from mycobacteria, phenol-soluble modulin from Staphylococcus epidermidis, glycoinositolphospholipids from Trypanosoma cruzi, as well as various lipopolysaccharides from non-enterobacteria (Takeda et al., 2003).

TLR2’s capability to recognize such a wide range of microbial PAMPs may be attributed

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to its ability to form heterodimers with TLR1 or TLR6. Studies in mice have shown that diacylated lipoproteins require TLR2/6 association for recognition, whereas triacylated lipoprotein recognition requires TLR2/1 association (Takeuchi et al., 2001; Takeda et al., 2002). The crystal structure of this heterodimer formation was eventually solved (Jin et al., 2007). Thus, heterodimer formation of TLR2 with either TLR1 or TLR6 allows for the recognition of a wide range of microbial PAMPs. It has been suggested that TLR2 may also form heterodimers with TLR10 and play a role in the recognition of triacylated lipopeptides (Guan et al., 2010).

1.7.3.1.2. TLR4

TLR4 is involved in the recognition of LPS on Gram-negative bacteria; however, like TLR2, it is able to recognize a variety of PAMPs from various microorganisms. LPS recognition by TLR4 requires the cooperation of several accessory molecules. Initially, LPS binds to LPS-binding protein (LBP) and this complex is then recognized by a CD14 receptor commonly expressed on monocytes, macrophages and neutrophils (Takeda and Akira, 2015). Once bound, the complex can associate in close proximity with TLR4.

Furthermore, for effective recognition and induction of an innate response, the presence of an additional protein, lymphocyte antigen 96 (MD-2), is needed (Nagai et al., 2002).

In addition to LPS, TLR4 has been shown to be involved in the recognition of taxol, a diterpene anti-tumor agent developed from the Pacific yew, Taxus brevifolia (Kawasaki et al., 2000). It has also been demonstrated that TLR4 can recognize endogenous ligands released during inflammatory responses and tissue damage, referred to as danger signals. These endogenous danger signals include heat shock proteins (HSP),

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HSP-60 and HSP-70, and extracellular matrix degradation products, biglycan, hyaluronan, and fibronectin (Ohashi et al., 2000; Okamura et al., 2001; Termeer et al., 2002; Vabulas et al., 2002; Schaefer et al., 2005). TLR4 is primarily expressed on the cell surface, however, studies have also shown that the TLR4/MD-2 complex can be localized intracellularly and play a role in sensing Gram-negative bacteria and LPS within the cell (Shibata et al., 2011).

1.7.3.1.3. TLR5

Mainly expressed by epithelial cells, TLR5 is responsible for the detection of the bacterial protein flagellin. Flagellin is the main component of bacterial flagellum, an organelle that is involved in propulsion. TLR5 is functionally expressed in intestinal, respiratory, and kidney/urogenital tract epithelial cells, as well as human macrophages and DCs (Vijay-Kumar and Gewirtz, 2009). Polymorphisms in the ligand-binding domain of TLR5 has been correlated with a susceptibility to pneumonia caused by the bacterium Legionella pneumophila (Hawn et al., 2003). Thus, TLR5 plays a critical role in the recognition and elimination of bacterium at the mucosal level.

1.7.3.1.4. TLR10

For the most part, subcellular localization and ligand recognition by TLR10 has only recently been elucidated. TLR10 was first cloned in 2001, however, since then little has been discovered about the receptor. Recent studies suggest that TLR10 works in cooperation with TLR2 in sensing triacylated lipopeptides (Guan et al., 2010).

Furthermore, TLR10 has been implicated as an important receptor involved in the

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induction of innate immune responses to influenza virus infection (Lee et al., 2014).

One reason why TLR10 continues to elude researchers is the absence of a suitable mouse model, as TLR10 is a pseudogene in mice due to the presence of gaps and retroviral insertions into its sequence.

1.7.3.2. Intracellular TLRs

1.7.3.2.1. TLR3

TLR3 is expressed intracellularly and recognizes double stranded RNA (dsRNA).

In resting cells, TLR3 is located in the endoplasmic reticulum and upon activation becomes localized in endosomal compartments where it initiates innate immune signaling (Zhang et al., 2013). It has been shown that polyinosinic-polycytidylic acid [poly (I:C)], a synthetic dsRNA analog, is a potent activator of TLR3-induced production of type I IFNs (Alexopoulou et al., 2001). Additionally, cell-endogenous mRNA double stranded regions have been shown to activate TLR3 signaling (Kariko et al., 2004).

TLR3 has been postulated to play a role in antiviral immunity, since dsRNA is a universal viral PAMP (Akira et al., 2006). Many viruses produce dsRNA during their replicative cycle as an intermediate in RNA synthesis or as a byproduct of symmetrical transcription of DNA virus genomes (Takeda et al., 2003). Although it has been demonstrated that TLR3 plays an indirect role in antiviral response (Zhang et al., 2013), it remains unclear the exact mechanisms of viral recognition. Interestingly, it has been shown that TLR3 knockout mice fail to show increased susceptibility to viral infections (Edelmann et al., 2004), which further discredits TLR3’s role in the recognition of viruses.

38 1.7.3.2.2. TLR7 and 8

Located in endosomes, TLR7 acts as an intracellular sensor of single-stranded RNA (ssRNA). TLR7 has been shown to recognize viral origin guanosine-rich and adenosine-rich ssRNA sequences from the human immunodeficiency virus (HIV), vesicular stomatitis virus (VSV), and influenza virus (Diebold et al., 2004; Heil et al., 2004; Lund et al., 2004). TLR7 mediated recognition of bacterial RNA in lysosomes has also been demonstrated in conventional DCs (Mancuso et al., 2009). In addition to ssRNA, synthetic compounds have been identified to be potent activators of TLR7 induced antiviral immunity. For instance, imidazoquinolone derivatives, such as imiquimod and resiquimod, are potent activators of proinflammatory cytokines through TLR7-mediated signaling.

Phylogenetically similar to TLR7, TLR8 also recognizes ssRNA in endosomes.

Both are structurally similar and recognize many of the same ligands. For example, TLR8 responds to imidazoquinolone derivatives and recognizes viral origin guanosine- rich and adenosine-rich ssRNA sequences from many viruses. Although TLR7 and TLR8 are expressed in human and mice, mouse TLR8 lacks the presence of 5 conserved amino acids rendering it nonfunctional (Kugelberg, 2014).

1.7.3.2.3. TLR9

Based on sequence homology, TLR9 is phylogenetically related to both TLR7 and TL8. Also expressed intracellularly, TLR9 is involved in the recognition of unmethylated cytosine-phosphate-guanine (CpG) motifs exhibited by some bacterial

39

and viral DNA. Studies have revealed that TLR9 can detect CpG DNA motifs of murine cytomegalovirus (MCMV), herpes simplex virus (HSV) type 1, and HSV type 2 (Hochrein et al., 2004; Krug et al., 2004; Tabeta et al., 2004). TLR9 is also involved in the recognition of self CpG DNA that can lead to the development of autoimmune disorders, including rheumatoid arthritis and systemic lupus erythematosus (Leadbetter et al., 2002; Boule et al., 2004).

1.7.3.2.4. TLR11 and 12

TLR11 is localized in endolysosomal compartments and functions to recognize proteins of uropathogenic and enteropathogenic bacteria (Broz and Monack, 2013). In mice, TLR11 has been shown to recognize uropathogenic bacteria in the bladder, as mice lacking TLR11 are highly susceptible to this infection (Zhang et al., 2004).

Additionally, TLR11 has been linked to the resistance to Toxoplasma gondii through recognition of the protein profilin (Yarovinsky et al., 2005). Like TLR5, TLR11 recognizes flagellin, however, both receptors function in different subcellular compartments. TLR12 is also located in endosomal compartments and can function alone or as a heterodimer with TLR11. TLR12 also plays a crucial role in resistance to Toxoplasma gondii through profilin recognition (Koblansky et al., 2013). As mentioned, TLR11 is not functional in humans as there is a stop codon inserted in the TLR11 gene sequence, while a TLR12 compatible sequence is not found in the human genome.

40 1.7.3.2.5. TLR13

The most recently identified, TLR13 functions inside the cell to recognize large bacterial ribosomal RNAs (rRNAs). More specifically, it recognizes conserved CGGAAAGACC motifs of 23S rRNA (Broz and Monack, 2013). A recent study has shown that the 23S rRNA of E. coli was able to induce the production of pro-IL1-β through a TLR13-dependant pathway. Like TLR11 and TLR12, TLR13 is not expressed in humans.

1.7.4. TLR Signaling

Binding of a TLR-specific ligand on the plasma membrane or in endosomal compartments leads to ligand-induced receptor dimerization and recruitment of cystolic TIR domain-containing adaptor molecules. The TIR domain of the activated TLR will signal through either the myeloid differentiation primary response protein 88 (MyD88) and MyD88-adaptor like/TIR-associated protein (MAL/TIRAP) or Toll-receptor- associated molecule (TRAM) and Toll-receptor-associated activator of interferon (TRIF) (O'Neill et al., 2013). With the exception of TLR3, all TLRs require MyD88 for downstream signaling as studies have shown that cells lacking MyD88 are only responsive to TLR3 ligands (Kawai et al., 1999; Akira et al., 2003). Following adaptor molecule recruitment, intracellular signaling results in the interaction of IL-1R-associated kinases (IRAKs) and the adaptor molecules TNF receptor-associated factors (TRAFs).

This leads to the activation of mitogen-activated protein kinases (MAPKs), JUN N- terminal kinase (JNK) and p38, and IRAKs (O'Neill et al., 2013). This results in the activation of transcription factor nuclear factor-κB (NF-κB), interferon regulatory factors

41

(IRFs), cyclic AMP-responsive element-binding protein (CREB), and activator protein 1 (AP1). Ultimately, TLR signaling leads to the induction of an innate immune response with the production of pro-inflammatory cytokines, including IL-1 and TNF-α, and type I IFNs.

1.8. TLRs and Antiviral Immunity

TLRs have been implicated in the detection of several viruses resulting in the subsequent induction of antiviral immunity. The antiviral innate immune response against viruses is characterized by the production IFNs, inflammatory cytokines and chemokines that aid in prevention of viral entry, replication and persistence. IFN production plays a critical role in the upregulation of hundreds of IFN-stimulated genes that have a wide spectrum of antiviral properties (Lester and Li, 2014). In addition, IFNs act in a paracrine manner to initiate an antiviral state in neighboring cells, as well as activation of various innate immune cells to mediate viral clearance. Furthermore, the production of inflammatory cytokines and chemokines aids in the facilitation of the innate immune responses and induction of adaptive immunity. Recognition of viral components by TLRs can occur on the surface of the cell (e.g., interaction with viral envelope proteins) or intracellularly (e.g., interaction with viral nucleic acids). In both situations, the resulting innate immune response is catered toward elimination of the virus.

42 1.8.1. TLRs and Hepadnaviruses

Historically, HBV was considered to be a ‘stealthy virus’ in the early phase of infection due to its inability to activate the innate immune response and induce the production of IFNs and IFN-stimulated genes (Wieland and Chisari, 2005). However, these observations were obtained in chimpanzees one week after infection with HBV, which was too late to correctly evaluate early innate responsiveness that usually is activated in minutes or hours post infection. In woodchucks experimentally infected with WHV, markers of the innate immune response were detected in the first few hours post- injection (Guy et al., 2008). In this study, WHV replication was detected in the liver as early as one hour after infection. Between 3-6 hours post infection, there was a significant increase in intrahepatic transcription of IFN-γ and IL-12 indicating activation of the innate immune response. By day 3, NK and NKT cells had become activated, which coincided with reduction of virus replication. Thus, in contrast to earlier reports, the innate immune system was found to play a role in early recognition of WHV.

Although direct binding of hepadnaviral antigens to TLRs has not yet been demonstrated, there is increasing evidence that TLRs play an important role in the immune response to HBV infection.

Viral lipoproteins and glycoproteins have been shown to be recognized by TLR2, thus, HBV glycoproteins seem like viable candidates for TLR ligands. Studies have implicated TLR2 in the induction of cytokines in macrophages due to HBV infection (Cooper et al., 2005). Additionally, TLR2 expression is downregulated in HBeAg- positive CHB patients when compared to HBeAg-negative CHB patients and healthy